Multiplexing information flow through dynamic signalling systems

by Giorgos Minas, Dan J. Woodcock, Louise Ashall, Claire V. Harper, Michael R. H. White, David A. Rand

We consider how a signalling system can act as an information hub by multiplexing information arising from multiple signals. We formally define multiplexing, mathematically characterise which systems can multiplex and how well they can do it. While the results of this paper are theoretical, to motivate the idea of multiplexing, we provide experimental evidence that tentatively suggests that the NF-κB transcription factor can multiplex information about changes in multiple signals. We believe that our theoretical results may resolve the apparent paradox of how a system like NF-κB that regulates cell fate and inflammatory signalling in response to diverse stimuli can appear to have the low information carrying capacity suggested by recent studies on scalar signals. In carrying out our study, we introduce new methods for the analysis of large, nonlinear stochastic dynamic models, and develop computational algorithms that facilitate the calculation of fundamental constructs of information theory such as Kullback–Leibler divergences and sensitivity matrices, and link these methods to new theory about multiplexing information. We show that many current models such as those of the NF-κB system cannot multiplex effectively and provide models that overcome this limitation using post-transcriptional modifications.

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Combining hypoxia-activated prodrugs and radiotherapy in silico: Impact of treatment scheduling and the intra-tumoural oxygen landscape

by Sara Hamis, Mohammad Kohandel, Ludwig J. Dubois, Ala Yaromina, Philippe Lambin, Gibin G. Powathil

Hypoxia-activated prodrugs (HAPs) present a conceptually elegant approach to not only overcome, but better yet, exploit intra-tumoural hypoxia. Despite being successful in vitro and in vivo, HAPs are yet to achieve successful results in clinical settings. It has been hypothesised that this lack of clinical success can, in part, be explained by the insufficiently stringent clinical screening selection of determining which tumours are suitable for HAP treatments. Taking a mathematical modelling approach, we investigate how tumour properties and HAP-radiation scheduling influence treatment outcomes in simulated tumours. The following key results are demonstrated in silico: (i) HAP and ionising radiation (IR) monotherapies may attack tumours in dissimilar, and complementary, ways. (ii) HAP-IR scheduling may impact treatment efficacy. (iii) HAPs may function as IR treatment intensifiers. (iv) The spatio-temporal intra-tumoural oxygen landscape may impact HAP efficacy. Our in silico framework is based on an on-lattice, hybrid, multiscale cellular automaton spanning three spatial dimensions. The mathematical model for tumour spheroid growth is parameterised by multicellular tumour spheroid (MCTS) data.

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Optimising efficacy of antibiotics against systemic infection by varying dosage quantities and times

by Andy Hoyle, David Cairns, Iona Paterson, Stuart McMillan, Gabriela Ochoa, Andrew P. Desbois

Mass production and use of antibiotics has led to the rise of resistant bacteria, a problem possibly exacerbated by inappropriate and non-optimal application. Antibiotic treatment often follows fixed-dose regimens, with a standard dose of antibiotic administered equally spaced in time. But are such fixed-dose regimens optimal or can alternative regimens be designed to increase efficacy? Yet, few mathematical models have aimed to identify optimal treatments based on biological data of infections inside a living host. In addition, assumptions to make the mathematical models analytically tractable limit the search space of possible treatment regimens (e.g. to fixed-dose treatments). Here, we aimed to address these limitations by using experiments in a Galleria mellonella (insect) model of bacterial infection, to create a fully parametrised mathematical model of a systemic Vibrio infection. We successfully validated this model with biological experiments, including treatments unseen by the mathematical model. Then, by applying artificial intelligence, this model was used to determine optimal antibiotic dosage regimens to treat the host to maximise survival while minimising total antibiotic used. As expected, host survival increased as total quantity of antibiotic applied during the course of treatment increased. However, many of the optimal regimens tended to follow a large initial ‘loading’ dose followed by doses of incremental reductions in antibiotic quantity (dose ‘tapering’). Moreover, application of the entire antibiotic in a single dose at the start of treatment was never optimal, except when the total quantity of antibiotic was very low. Importantly, the range of optimal regimens identified was broad enough to allow the antibiotic prescriber to choose a regimen based on additional criteria or preferences. Our findings demonstrate the utility of an insect host to model antibiotic therapies in vivo and the approach lays a foundation for future regimen optimisation for patient and societal benefits.

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Heritable gene expression variability and stochasticity govern clonal heterogeneity in circadian period

by K. L. Nikhil, Sandra Korge, Achim Kramer

A ubiquitous feature of the circadian clock across life forms is its organization as a network of cellular oscillators, with individual cellular oscillators within the network often exhibiting considerable heterogeneity in their intrinsic periods. The interaction of coupling and heterogeneity in circadian clock networks is hypothesized to influence clock’s entrainability, but our knowledge of mechanisms governing period heterogeneity within circadian clock networks remains largely elusive. In this study, we aimed to explore the principles that underlie intercellular period variation in circadian clock networks (clonal period heterogeneity). To this end, we employed a laboratory selection approach and derived a panel of 25 clonal cell populations exhibiting circadian periods ranging from 22 to 28 h. We report that a single parent clone can produce progeny clones with a wide distribution of circadian periods, and this heterogeneity, in addition to being stochastically driven, has a heritable component. By quantifying the expression of 20 circadian clock and clock-associated genes across our clone panel, we found that inheritance of expression patterns in at least three clock genes might govern clonal period heterogeneity in circadian clock networks. Furthermore, we provide evidence suggesting that heritable epigenetic variation in gene expression regulation might underlie period heterogeneity.

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Cell–substrate adhesion drives Scar/WAVE activation and phosphorylation by a Ste20-family kinase, which controls pseudopod lifetime

by Shashi Prakash Singh, Peter A. Thomason, Sergio Lilla, Matthias Schaks, Qing Tang, Bruce L. Goode, Laura M. Machesky, Klemens Rottner, Robert H. Insall

The Scar/WAVE complex is the principal catalyst of pseudopod and lamellipod formation. Here we show that Scar/WAVE’s proline-rich domain is polyphosphorylated after the complex is activated. Blocking Scar/WAVE activation stops phosphorylation in both Dictyostelium and mammalian cells, implying that phosphorylation modulates pseudopods after they have been formed, rather than controlling whether they are initiated. Unexpectedly, phosphorylation is not promoted by chemotactic signaling but is greatly stimulated by cell:substrate adhesion and diminished when cells deadhere. Phosphorylation-deficient or phosphomimetic Scar/WAVE mutants are both normally functional and rescue the phenotype of knockout cells, demonstrating that phosphorylation is dispensable for activation and actin regulation. However, pseudopods and patches of phosphorylation-deficient Scar/WAVE last substantially longer in mutants, altering the dynamics and size of pseudopods and lamellipods and thus changing migration speed. Scar/WAVE phosphorylation does not require ERK2 in Dictyostelium or mammalian cells. However, the MAPKKK homologue SepA contributes substantially—sepA mutants have less steady-state phosphorylation, which does not increase in response to adhesion. The mutants also behave similarly to cells expressing phosphorylation-deficient Scar, with longer-lived pseudopods and patches of Scar recruitment. We conclude that pseudopod engagement with substratum is more important than extracellular signals at regulating Scar/WAVE’s activity and that phosphorylation acts as a pseudopod timer by promoting Scar/WAVE turnover.

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Selfing mutants link Ku proteins to mating type determination in Tetrahymena

by I-Ting Lin, Meng-Chao Yao

Recognition of self and nonself is important for outcrossing organisms, and different mating types establish the barrier against self-mating. In the unicellular ciliate T. thermophila, mating type determination requires complex DNA rearrangements at a single mat locus during conjugation to produce a type-specific gene pair (MTA and MTB) for 1 of 7 possible mating types. Surprisingly, we found that decreased expression of the DNA breakage-repair protein Ku80 at late stages of conjugation generated persistent selfing phenotype in the progeny. DNA analysis revealed multiple mating-type gene pairs as well as a variety of mis-paired, unusually arranged mating-type genes in these selfers that resemble some proposed rearrangement intermediates. They are found also in normal cells during conjugation and are lost after 10 fissions but are retained in Ku mutants. Silencing of TKU80 or TKU70-2 immediately after conjugation also generated selfing phenotype, revealing a hidden DNA rearrangement process beyond conjugation. Mating reactions between the mutant and normal cells suggest a 2-component system for self–nonself-recognition through MTA and MTB genes.

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